Wide-area Sentinel-1 SAR mosaics patches over Finland for semantic segmentation

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Abstract 

Here, a dataset used in manuscript "Wide-Area Land Cover Mapping with Sentinel-1 Imagery using Deep Learning Semantic Segmentation Models" Scepanovic et al. (https://doi.org/10.1109/JSTARS.2021.3116094) is published. The data contains preprocessed SAR backscatter digital numbers as 7000 geotiff image patches of size 512x512 (about 10 km x 10 km size) sampled from several wide-area SAR mosaics compiled from all summer Sentinel-1A images  acquired over Finland in the summer of 2018. The geographical area where image patches are sampled covers the territory of Finland located to the south of 66.0∘latitude, which is nearly the whole country without Finnish Lapland. Southern Finland is primarily covered by boreal forests with lakes, marshes, open bogs, agricultural areas, and urban settlements. The SAR data are accompanied by reference ("ground truth") dataset representing 5 basic land cover classes produced based on Finnish version of CORINE Land Cover map, 2018.

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